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Quantitative estimation of activity and quality for collections of functional genetic elements

Nature Methods volume 10, pages 347–353 (2013)Cite this article

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Abstract

The practice of engineering biology now depends on the ad hoc reuse of genetic elements whose precise activities vary across changing contexts. Methods are lacking for researchers to affordably coordinate the quantification and analysis of part performance across varied environments, as needed to identify, evaluate and improve problematic part types. We developed an easy-to-use analysis of variance (ANOVA) framework for quantifying the performance of genetic elements. For proof of concept, we assembled and analyzed combinations of prokaryotic transcription and translation initiation elements in Escherichia coli. We determined how estimation of part activity relates to the number of unique element combinations tested, and we show how to estimate expected ensemble-wide part activity from just one or two measurements. We propose a new statistic, biomolecular part 'quality', for tracking quantitative variation in part performance across changing contexts.

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Figure 1: Composition of irregular transcription and translation genetic elements.
Figure 2: Observed variation and correlation of mRNA abundance and protein fluorescence from a full combinatorial library of expression control elements.
Figure 3: Quantification of factors and interactions contributing to variation in mRNA abundance, translation efficiency and gene expression.
Figure 4: Performance and quality scores for transcriptional and translation control elements.
Figure 5: Estimation of part activity with limited measurements.

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Acknowledgements

We thank N. Hillson, V. Rhodius and C. Smolke for comments and discussion, and F. St-Pierre (Stanford University) for the plasmid pIT-KL-I52002. We acknowledge support from the National Science Foundation to the BIOFAB (award EEC 0946510). G.C. acknowledges support from the Human Frontier Science Program (LT000873/2011-l) and the Bettencourt Schueller foundation. A.P.A. and D.E. acknowledge support from the Synthetic Biology Engineering Research Center under National Science Foundation grant 04-570/0540879. J.C.G. acknowledges financial support from the Portuguese Fundação para a Ciência e a Tecnologia (SFRH/BD/47819/2008). This work was conducted at the Joint BioEnergy Institute supported by the Office of Science, Office of Biological and Environmental Research of the US Department of Energy, under contract DE-AC02-05CH11231.

Author information

Author notes

  1. Lance Martin, Ayumi Yu, Cesar Rodriguez & Gaymon Bennett

    Present address: Present addresses: Department of Bioengineering, Stanford University, Stanford, California, USA (L.M.); Philotic, Inc., San Francisco, California, USA (A.Y.); Autodesk, Inc., San Francisco, California, USA (C.R.); and Center for Biological Futures, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA (G.B.).,

  2. Vivek K Mutalik, Joao C Guimaraes, Guillaume Cambray, Drew Endy and Adam P Arkin: These authors contributed equally to this work.

Authors and Affiliations

  1. BIOFAB International Open Facility Advancing Biotechnology, Emeryville, California, USA

    Vivek K Mutalik, Joao C Guimaraes, Guillaume Cambray, Quynh-Anh Mai, Marc Juul Christoffersen, Lance Martin, Ayumi Yu, Colin Lam, Cesar Rodriguez, Gaymon Bennett, Jay D Keasling, Drew Endy & Adam P Arkin

  2. Physical Biosciences Division, Lawrence Berkeley National Laboratory, Berkeley, California, USA

    Vivek K Mutalik, Jay D Keasling & Adam P Arkin

  3. Department of Bioengineering, University of California, Berkeley, Berkeley, California, USA.,

    Vivek K Mutalik, Joao C Guimaraes, Guillaume Cambray, Quynh-Anh Mai, Marc Juul Christoffersen, Lance Martin, Ayumi Yu, Colin Lam, Cesar Rodriguez, Gaymon Bennett, Jay D Keasling & Adam P Arkin

  4. Department of Informatics, Computer Science and Technology Center, University of Minho, Campus de Gualtar, Braga, Portugal

    Joao C Guimaraes

  5. Department of Chemical & Biomolecular Engineering, University of California, Berkeley, Berkeley, California, USA.,

    Jay D Keasling

  6. Joint BioEnergy Institute, Emeryville, California, USA

    Jay D Keasling

  7. Department of Bioengineering, Stanford University, Stanford, California, USA

    Drew Endy

Authors
  1. Vivek K Mutalik
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Contributions

V.K.M., D.E. and A.P.A. conceived the study; V.K.M., G.C. and Q.-A.M. designed experiments; V.K.M., G.C., Q.-A.M., L.M., A.Y. and C.L. performed experiments; J.C.G. and G.C. built the computational model; V.K.M., G.C., J.C.G., D.E. and A.P.A. analyzed and interpreted the data; C.R. and M.J.C. provided software tools and database support; G.B. provided critical feedback on the framing the project; and V.K.M., J.C.G., G.C., J.D.K., D.E. and A.P.A. wrote the manuscript. All authors discussed and commented on the manuscript.

Corresponding authors

Correspondence to Drew Endy or Adam P Arkin.

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Mutalik, V., Guimaraes, J., Cambray, G. et al. Quantitative estimation of activity and quality for collections of functional genetic elements. Nat Methods 10, 347–353 (2013). https://doi.org/10.1038/nmeth.2403

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